Probabilistic neuron circuits

ABSTRACT

Neuron circuit structures are presented which employ magnetic tunnel junction (MTJ) elements that change state probabilistically in response to application of electrical source currents that emulate synaptic activity. Some implementations form probabilistic neuron circuits using homogeneous perpendicular spin-transfer torque (STT) MTJ elements. These neuron circuits include a perpendicular STT reference MTJ element coupled via an electrical node with a perpendicular STT neuron MTJ element that can change state. The electrical node for each neuron circuit couples a neuron MTJ element or “perturbation” element to a reference element, and also to an electrical current employed to influence probabilistic magnetization state changes in the perturbation MTJ element. A read current can be applied to the perturbation element to produce an output voltage at the electrical node indicative of a magnetization state of the perturbation element.

TECHNICAL FIELD

Aspects of the disclosure are related to the field of artificialelectrical/magnetic neuron circuitry in artificial neural networks.

BACKGROUND

Artificial neural networks (ANN) can be formed from individualartificial neurons that are emulated using software, integratedhardware, or other discrete elements. Biological neurons typicallyproduce a ‘spike’ output in response to various synaptic inputs to theneuron cell body, and these artificial neurons attempt to emulate thisbehavior.

Past research on hardware implementation of spiking neurons has mainlyfocused on deterministic neural models, and often employedarea-expensive complementary metal-oxide-semiconductor (CMOS)implementations involving a large number of transistors for each neuron.Further, such deterministic neuron models were unable to fully emulateneural computation in biological systems, which are significantly proneto noise arising from associated synapses, dendrites, or neuron cells.

More recent theoretical studies have been performed to demonstrate thatBayesian computation can be performed in neural networks inspired fromcortical microcircuits of pyramidal “stochastic” neurons. Such neurons,observed in the biological cortex, spike stochastically, and theprobability of firing at a particular time is a non-linear function ofthe instantaneous magnitude of the resultant post-synaptic current inputto the neuron.

Attempts at employing magnetic tunnel junctions (MTJs) into neuroncircuits have been undertaken. MTJs operate using tunnelmagnetoresistance (TMR), which is a magneto-resistive effect. MTJstypically consist of two ferromagnets separated by a thin insulatorthrough which electrons can quantum-mechanically tunnel from oneferromagnet into the other. In the presence of thermal noise, aswitching behavior of an MTJ due to flow of an input current can beobserved to be stochastic in nature, and the probability of switchingincreases with the magnitude of the input current. Thus, MTJs canemulate functionality of “stochastic” neurons observed in a biologicalcortex, where an MTJ neuron “spikes” probabilistically depending on asynaptic input, in a manner similar to biological neurons.

However, present approaches place an in-plane spin-transfer torque (STT)reference MTJ in series with an in-plane spin orbit torque (SOT) neuronMTJ that has an additional heavy metal underlayer, referred to as aheterogeneous in-plane MTJ scheme. In these schemes, separate “write”and “read” current paths are employed, and have resultant poorscalability and high switching currents. Other approaches replace theSOT in-plane neuron MTJ with an SOT perpendicular MTJ that has anexternal electric field applied. However, this external fieldsignificantly degrades thermal stability of neighboring neuroncircuitry.

Overview

Neuron circuit structures are presented which employ magnetic tunneljunction (MTJ) elements that change state probabilistically in responseto application of electrical source currents that emulate synapticactivity. Some implementations form probabilistic neuron circuits usinghomogeneous perpendicular spin-transfer torque (STT) MTJ elements. Theseneuron circuits include a perpendicular STT reference MTJ elementcoupled via an electrical node with a perpendicular STT neuron MTJelement that can change state. The electrical node for each neuroncircuit couples a neuron MTJ element or “perturbation” element to areference element, and also to an electrical current employed toinfluence probabilistic magnetization state changes in the perturbationMTJ element. A read current can be applied to the perturbation elementto produce an output voltage at the electrical node indicative of amagnetization state of the perturbation element.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the disclosure can be better understood with referenceto the following drawings. The components in the drawings are notnecessarily to scale, emphasis instead being placed upon clearlyillustrating the principles of the present disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views. While several embodiments are described inconnection with these drawings, the disclosure is not limited to theembodiments disclosed herein. On the contrary, the intent is to coverall alternatives, modifications, and equivalents.

FIG. 1 illustrates an example probabilistic neuron system.

FIG. 2 illustrates an example operation of a probabilistic neuronsystem.

FIG. 3 illustrates an example probabilistic neuron circuit.

FIG. 4 illustrates example control operations of a probabilistic neuroncircuit.

FIG. 5 illustrates example state operations of magnetic tunnel junctionelements.

FIG. 6 illustrates an example array of neuron circuits on asemiconductor substrate.

DETAILED DESCRIPTION

Discussed herein are various enhanced probabilistic neuron circuits andassociated interconnect and control systems. These neuron circuitsemploy perpendicular spin transfer torque (STT) magnetic tunnel junction(MTJs) elements to emulate behavior of biological neurons. In eachneuron circuit, at least one perturbation magnetic tunnel junctionelement is included, referred to herein as a perturbation magnetictunnel junction element. A perturbation magnetic tunnel junctionelement, or perturbation MTJ element, is an MTJ element with analterable magnetization state. At least one reference magnetic tunneljunction element can also be included. A reference magnetic tunneljunction element, referred to herein as a reference MTJ element, is anMTJ element with a magnetization state held in a predetermined state. Aperturbation MTJ element is employed in a particular arrangement with areference MTJ element to form a neuron circuit. As will be discussedherein, changes in a magnetization state of a perturbation MTJ withrespect to a reference MTJ can produce probabilistic outputs based inpart on stochastic properties of the neuron circuits.

As used herein, magnetic tunnel junction elements, such as aperturbation element, perturbation MTJ element, perturbation magnetictunnel junction (MTJ) element, reference element, reference MTJ element,or reference magnetic tunnel junction (MTJ) element discussed below, areeach components of circuits that consist of two layers of ferromagneticmaterials separated by a thin insulator through which electrons cantunnel from one ferromagnetic layer into the other ferromagnetic layer.One ferromagnetic layer of an MTJ can be referred to as a pinned layerwhich has a fixed magnetization state, while another ferromagnetic layerof an MTJ comprises a free layer which can change in magnetizationstate. An intermediate layer comprising a thin insulator separating thetwo ferromagnetic layers can be formed from an oxide material or othersuitable electrical insulator. Electrical terminals can be formed tointerface the free and pinned layers of the MTJ to other components in acircuit.

Specific arrangements of MTJs are included in the probabilistic neuroncircuits discussed herein, namely perpendicular magnetic tunnel junctionarrangements. The perpendicular arrangement refers to perpendicularmagnetic anisotropy, where MTJs employed have a preferred direction ofalignment of magnetization within the MTJ. In perpendiculararrangements, the preferred direction of alignment of associatedmagnetic moments are perpendicular to a surface of a correspondingsemiconductor substrate. Spin-transfer torque (STT) refers herein todevices in which spin polarized currents reversibly switch amagnetization state of a ferromagnetic layer, namely the magnetizationstate of the free layers discussed herein. In the presence of thermalnoise, a switching behavior of the free layer of a perturbation MTJ dueto flow of an input current through an associated pinned layer can beobserved to be stochastic in nature, and the probability of switchingmagnetization states in the perturbation MTJ increases with themagnitude of the input current. Thus, the perpendicular STT MTJsdiscussed herein can emulate functionality of “stochastic” neuronsobserved in a biological cortex, where an MTJ neuron “spikes”probabilistically depending a synaptic input, similar to biologicalneurons.

The neuron circuits discussed herein employ arrangements ofperpendicular STT MTJs to provide enhanced operation and emulatebiological neurons, while having better scalability, manufacturability,and lower switching current than other previous approaches. Theseprevious approaches include the examples described above forheterogeneous in-plane MTJ schemes that include spin orbit torque (SOT)MTJs. Moreover, the neuron circuits that employ perpendicular STT MTJsherein can be assembled into tighter vertical stack-ups. These verticalstack-ups allow for multi-layered “bitline” arrangements, where sourcecurrent circuitry can be formed into horizontal bitlines andcorresponding neuron circuitry can be fit into the vertical pitch ofeach horizontal bitline. In this manner, large vertical stack-ups ofneuron circuits can be built up from semiconductor substrates. Variousinterconnect and control logic can be formed on the same semiconductorsubstrate, allowing for large integrated neuron circuits to beestablished in a compact integrated circuit.

FIG. 1 is presented as a first example of a probabilistic neuron systemthat employs MTJ elements. FIG. 1 is a system diagram illustratingartificial neuron system 100. System 100 includes synaptic circuit 110,neuron circuit 120, and output circuit 130. Control system 140 is alsoinclude as representative of one or more circuits, software, firmware,hardware, or other elements that may control the operations of synapticcircuit 110, neuron circuit 120, and output circuit 130. Synapticcircuit 110 is coupled over link 165 to neuron circuit 120, and neuroncircuit 120 is coupled over link 166 to output circuit 130. Controlsystem 140 controls operation of synaptic circuit 110 over one or morelinks 161. Control system 140 also provides control to neuron circuit120 over one or more links 162. An output from output circuit 130 can beprovided to control system 140 over link 163, or might instead beprovided to other circuitry, including other neuron systems. When a hostsystem is employed, communication can occur over link 164. This hostsystem might comprise one or more computer systems, software elements,or other hardware/software control systems.

In operation, synaptic circuit 110 comprises a synaptic current source.A synaptic current source used herein is any current source thatestablishes an electrical current emulating a synaptic input to aperturbation MTJ element, which might consist of combined outputs ofmemory bits, circuitry configured to introduce neuron circuit writecurrents responsive to control/command instructions, transistor currentsources, voltage sources which can establish currents resultant from acorresponding source voltage coupled to a free layer of a perturbationMTJ element, or other sources. This synaptic current can be provided toneuron circuit 120 over link 165, which may include one or moreswitching elements to allow control system 140 to selectively providethe synaptic current during an appropriate neuron circuit write phase.In some examples, synaptic circuit 110 provides a voltage level overlink 165 which is used by neuron circuit 120 to establish the synapticcurrent.

To establish the synaptic current as a current source, a plurality ofdata bits may be included in synaptic circuit 110, forming a controlline, synaptic bitline, or other suitable circuit arrangement. Thesedata bits can be set or otherwise established at target levels bycontrol system 140 via control link 161. Control system 140 can controlsynaptic weights in synaptic circuit 110 over link 161, as well ascontrol write pulse widths to further control synaptic circuit 110 overlink 161. In further examples, inputs to bits of synaptic circuit 110can comprise outputs of various neuron circuits, forming a network ofinterconnected neuron circuits.

Once the synaptic current of a selected write pulse width has beenestablished by a synaptic current source and sent to neuron circuit 120,a state of a perturbation element comprising neuron circuit 120 canprobabilistically change state from an initial state, or remain in theinitial state. This perturbation element can comprise a perpendicularspin transfer torque (STT) MTJ element, which has an alterablemagnetization as the state. A first ferromagnetic layer of the MTJ is afree ferromagnetic layer (referred to herein as a free layer), andcomprises a ferromagnetic material that permits a magnetic moment of thecorresponding ferromagnetic material to change orientation in responseto an electromagnetic force. This change in magnetic moment orientationis referred to herein as a magnetization state, which changes relativeto a second ferromagnetic layer of the MTJ element. This secondferromagnetic layer is referred to herein as a pinned layer, althoughother common nomenclature can be used, such as a reference layer or afixed layer. The pinned layer of the MTJ element is a layer offerromagnetic material that holds a magnetic moment of the correspondingferromagnetic material in a predetermined or fixed state even under theinfluence of the electromagnetic force which might change the state ofthe free layer. When the free layer and the pinned layer are in the samemagnetization state, then the MTJ element is considered to be in aparallel state. When the free layer and the pinned layer are in adifferent magnetization state, then the MTJ element is considered to bein an anti-parallel state. Thus, the alterable magnetization state ofMTJ elements discussed herein can change among two states, namely aparallel state and an anti-parallel state.

Due to the probabilistic configuration of neuron circuit 120, eachparticular application of the synaptic current to the associatedperturbation element may (or may not) change the state of theperturbation element. Thermal noise present in neuron circuit 120, alongwith any thermal noise variations in the synaptic current itself can addprobabilistic or stochastic variability to the state changing behaviorof the perturbation element of neuron circuit 120. Properties of thesynaptic current, such as magnitude and duration when introduced toneuron circuit 120, can influence the probabilistic or stochasticswitching behavior of the associated perturbation element. Thus,repeated neuron write attempts can be performed followed bycorresponding neuron read attempts to produce an output.

When a change in state occurs in the perturbation element, a readattempt will produce an output that indicates a change in magnetizationstate. This output might comprise a voltage spike resultant fromapplication of a read current to the perturbation element. A voltagespike output can comprise a short-duration increase in voltage at anoutput node resultant from a read current passing through a perturbationMTJ element in series with a reference MTJ element coupled to areference potential. This output can be provided by an output node fortransfer over link 166 and further conditioning, voltage levelconversion, or other handling by output circuit 130. A read current of aselected read pulse width can be provided by a read current source ofcontrol system 140 over link 162. As used herein, a read current sourcecomprises circuitry that sends a read current through at least aperturbation MTJ element, such as a circuitry configured to produce readcurrents responsive to control/command instructions, transistor currentsources, voltage sources which can establish currents resultant from avoltage introduced to a pinned layer of a perturbation MTJ element inseries with a reference MTJ element, or other sources.

After an output is produced, such as the voltage spike output, a resetcurrent can be applied along the same pathway as the read current. Thisreset current can be established having a selected reset pulse with andsent by control system 140 over link 162. This reset current resets theMTJ element into an initial magnetization state, and can be provided bya reset current source. The reset current source comprises similarcircuitry as the read current source, but consists of a higher magnitudevoltage or current introduced to a pinned layer of a perturbation MTJelement in series with a reference MTJ element.

To further describe operation of the elements of FIG. 1, flow diagram200 is presented in FIG. 2. FIG. 2 illustrates an example operation of aprobabilistic neuron system. The operations of FIG. 2 can be applied toelements of any of the example neuron systems or neuron circuits herein.However, for clarity, the operations of FIG. 2 will be discussed in thecontext of elements of FIG. 1. Operations of FIG. 2 can be controlled bycontrol system 140 over links 161-163 or by an associated host over link164.

Write operations, read operations, and reset operations are performedthat involve associated ‘phases’ of control of neuron circuit 120. Resetoperations are performed to place a perturbation MTJ element of neuroncircuit 120 into a chosen initial magnetization state. Reset operationsare performed before usage of neuron circuit 120, as well as after amagnetization state change in the perturbation MTJ element. Writeoperations are performed to attempt to induce a magnetization statechange in the perturbation MTJ element of neuron circuit 120, such as toproduce a probabilistic change in magnetization state of theperturbation MTJ element due in part to stochastic properties of neuroncircuit 120. The magnetization state of the perturbation MTJ element canchange from the initial state established by the reset operation to aresultant state after completion of the write operation which applies asynaptic current to neuron circuit 120. Read operations are performedafter each write operation to determine if the perturbation MTJ elementhas changed magnetization state responsive to the write operation.

Turning now to the operations of FIG. 2, the three phases of operationmentioned above are presented: a write phase, a read phase, and a resetphase. During a write phase, a synaptic current of a selected writepulse duration is sent (201) from synaptic circuit 110 through anelectrical node to a perturbation magnetic tunnel junction (MTJ) elementof neuron circuit 120 which stochastically influences a magnetizationstate of the perturbation MTJ element. Application of the synapticcurrent to neuron circuit 120 can be controlled via link 161. Theperturbation MTJ element might be coupled via the electrical node with areference element, which might comprise another MTJ element of neuroncircuit 120. However, the reference element could be any active orpassive electrical component, such as a resistor or resistors. Thesynaptic current can be generated as an output from a plurality of dataelements coupled in parallel to link 165. Each of the plurality of dataelements can output a corresponding portion of the synaptic current thatstochastically influences a change in the magnetization state of theperturbation MTJ element. Each of the plurality of data elements can beset to a desired state over link 161 prior to application of thesynaptic current over link 165.

After the synaptic current has been applied to the perturbation MTJelement in the write phase, a read phase can occur. During the readphase, synaptic circuit 110 is first isolated (202) from the electricalnode and thus the perturbation MTJ element. A read current of a selectedread pulse duration is produced and sent (203) over link 162 through theperturbation MTJ element and the reference MTJ element coupled by theelectrical node. This read current might produce a change in an outputvoltage at the node that indicates a change in magnetization state froman initial state of the perturbation MTJ. At the node, the outputvoltage might comprise an output voltage spike which can be detected bycontrol system 140 through output circuit 130 and link 163. If thevoltage spike occurs (204), then a corresponding output produced byoutput circuitry 130 can be used to drive further circuitry orprocesses. An indication of this output voltage spike can be convertedby output circuitry 130 into other output formats, logic levels for useby further circuitry or processes. If the voltage spike is not producedresponsive to the read current, then control system 140 can determinethat a change in magnetization state of the perturbation MTJ element didnot occur. The write phase and read phase are repeated until a voltagespike occurs at the node during the read phase.

Once a voltage spike is detected, or any corresponding output fromoutput circuit 130, a reset phase can be performed. A reset current of aselected reset pulse duration is established which places theperturbation MTJ element into a desired initial magnetization state inpreparation for another write-read cycle. Furthermore, individual dataelements of synaptic circuit 110 can be set to desired bit levels duringthe reset phase. To reset the perturbation MTJ element, a reset currentis applied (205) via link 162. The reset current is similar in nature tothe read current, but larger in magnitude than the read current.Responsive to the reset current, the perturbation MTJ element is placedinto a corresponding magnetization state.

To further describe the elements discussed for FIGS. 1 and 2, a moredetailed circuit representation is now presented. FIG. 3 illustratesexample probabilistic neuron circuitry, represented by circuitry 300.Circuitry 300 includes synaptic circuit 310, neuron elements 320, andoutput elements 330. In some examples, synaptic circuit 310 comprises anexample implementation of synaptic circuit 110 of FIG. 1, neuronelements 320 comprise an example implementation of neuron circuit 120,and output elements 330 comprise an example implementation of outputcircuit 130, although variations are possible. Various inputs andoutputs to the elements of circuitry 300 can be provided by a host orcontrol system, such as control system 140 of FIG. 1, among othercontrol logic and circuitry.

FIG. 3 also includes a detailed view of perturbation element 322, whichcan be representative of any MTJ discussed herein. As seen in view 301,a free ferromagnetic layer and a pinned ferromagnetic layer are formedwith a tunnel barrier layer separating the two ferromagnetic layers. Foreach of the MTJ elements in FIG. 3, the free layer is labeled with an F,the tunnel barrier layer is labeled with a T, and the pinned layer islabeled with a P. The pinned layer typically has a fixed or otherwiseunchanging magnetization, which is shown in an example orientation inFIG. 3. The free layer has an alterable or changeable magnetization,which is shown accordingly in FIG. 3. The reference MTJ elementdiscussed herein can comprise an MTJ element similar to the perturbationMTJ element, but having a magnetization state held in a predeterminedstate due to the selection of applied control voltages. However, thereference MTJ element or reference magnetic tunnel junction (MTJ)element used herein can instead comprise any reference element to form avoltage divider with the perturbation MTJ element that has an outputvoltage at an output node, such as a resistor, resistor network,transistor circuitry, passive or active electrical components, or othercircuitry.

Synaptic circuit 310 comprises a plurality of 1-n MTJ elements coupledin a parallel fashion, with four example MTJs, represented by MTJs311-314 in FIG. 3. Synaptic bitline 340 couples a free layer terminal ofeach of MTJs 311-314 to each other, while a select line couples aswitching element to a pinned layer terminal for each of MTJs 311-314.Synaptic bitline 340 might be referred to as a bitline in some examples,such as when MTJs 311-314 comprise a plurality of memory bits arrangedinto a bitline. This bitline can have a number of data bitscorresponding to the number of MTJ elements. Switching elements orselection elements, namely transistors 315-318, are included to allowmagnetization states of each of MTJs 311-314 to be altered independentlyof each other. These magnetization states can be altered by controllingactivation of wordlines (WL) 0-n and placing ‘data’ bits on synapticsource line 341 that are reflective of the desired magnetization statesto be written into selected ones of MTJ 311-314. In this manner, each ofMTJs 311-314 can have different magnetization states established whichreflect individual data bits stored therein. MTJs 311-314 can provide anoutput via synaptic bitline 340 that is reflective of a compositesummation or combination output from all of MTJs 311-314.

The individual MTJs can be set into parallel or antiparallelmagnetization states to produce a ‘synaptic’ voltage (V_(SYN)) which inturn produces an associated synaptic current or write current(I_(WRITE)) to node 325 when transistor 319 is enabled. The combinationoutput of MTJs 311-314 can be employed to provide a synaptic currentwith a magnitude and duration which is based in part on the data bitsstored by MTJs 311-314. It should be noted that the output of synapticbitline 340 can comprise V_(SYN), which after passing through transistor319, produces I_(WRITE). Instead of MTJ elements, any memory device canbe employed to store individual data bits and produce an output asV_(SYN), such as flash memory cells, phase change memory cells, magneticmemory cells, or other data bit storage elements. Furthermore, anynumber of MTJs might be provided in a bitline or other structuralarrangement. These number of MTJs can be included to adjust properties,granularity, resolution, or other properties of V_(SYN) and consequentlyI_(WRITE). In other examples, a write voltage (V_(SYN)) might not beproduced by associated data bit elements, and instead a synaptic currentmight be more directly produced.

As mentioned above, data bits that are input to each of MTJs 311-314 canbe selected to produce a desired output synaptic current. Also, the databits might be derived or received from other active circuitry, such asoutputs from further neuron circuitry. For example, an output producedby output elements 330 might be used as an input to one or more furtherneuron circuits. This input can be placed onto a select line of anotherneuron, or more than one neuron. In this manner, many neuron circuitscan be interconnected via inputs and outputs to establish a largenetwork or neural net of neuron circuits. In other examples, bits arewritten into MTJs 311-314 from outputs of other neurons tied to WLselectors for associated transistors, and a particular logic level(high/low) is held on synaptic source line 341. As will be discussed inFIG. 6 below, a compact integrated neuron system can be establishedusing these arrangements.

Turning now to operation of neuron elements 320, both reference element321 and perturbation element 322 are included. Reference element 321 andperturbation element 322 both comprise perpendicular STT MTJs. Referenceelement 321 has free layer 351, pinned layer 352, and tunnel layer 353.Perturbation element 322 has free layer 354, pinned layer 355, andtunnel layer 356. Reference element 321 and perturbation element 322 arecoupled to node 325 via terminals associated with free layers 351 and354. Due to both reference element 321 and perturbation element 322comprising perpendicular STT MTJs, a ‘homogenous’ configuration isachieved. In this example, the free layer of each of reference element321 and perturbation element 322 are coupled via node 325, althoughvariations are possible. Transistors 323 and 324 are provided toselectively couple reference element 321 and perturbation element 322 toappropriate voltages (V4/V5) during operation. Reference element 321 andperturbation element 322 can form a voltage divider at node 325 when aread current is directed through perturbation element 322 and referenceelement 321. Control of transistors 323 and 324 is provided via nodes V2and V3, respectively, and can be established by a control system orcircuitry, such as that discussed above for control system 140. Furtherdiscussion of timing and control of nodes V1-V5 is discussed in FIG. 4below.

During operation, a repetitive cycle of a write phase and a read phaseis performed until perturbation element 322 changes state. The writephase includes application of a synaptic current or neuron write current(I_(WRITE)) to node 325 as provided by synaptic circuit 310. Thisapplication of I_(WRITE) is controlled by operation of node V1 andtransistor 319. Once applied, I_(WRITE) can influence a magnetizationstate of perturbation element 322, while reference element 321 isdecoupled from V4 by deactivation of transistor 323. Thermal noise,among other noise sources, is also present within perturbation element322 and I_(WRITE), and this thermal noise can contribute to a stochasticperformance of perturbation element 322. This stochastic performanceleads to a quasi-random or probabilistic switching of states byperturbation element 322 from an initial magnetization state to a finalmagnetization state when I_(WRITE) is applied. To determine ifperturbation element 322 has switched states, a read current (I_(READ))is applied by coupling node V5 to a terminal associated with pinnedlayer 355 of perturbation element 322. This read current is provided tonode 325, and reference element 321 is coupled to an electricalreference or ground potential through node V4 and transistor 323. Whenperturbation element 322 has changed states, then a voltage spike isproduced at node 325 which is provided as a desired logic level usingoutput elements 330. Once an output indicative of a state change byperturbation element 322 is detected, then perturbation element 322 canbe reset into the initial magnetization state using a reset current(I_(RESET)) introduced to node 325 by a voltage at node V5. After thereset current has been applied, a current write phase/read phase cyclecan be halted or begun anew, as desired.

Although a logic inverter 331 is shown as comprising output elements330, other signal conditioning and conversion elements can be included.These other elements might comprise tristate buffers, logic gates,voltage conversion circuitry, analog-to-digital conversion circuitry,operational amplifiers, or other elements, including combinationsthereof. Output elements 330 might be included in neuron elements 320,or even omitted, if a next circuit in series with neuron elements 320includes appropriate circuitry. Also, transistor 319 is shown asincluded in either synaptic circuit 310 or neuron elements 320,depending upon implementation.

Transistors 315-319 and 323-324 each can comprise one or more switchingelements or selection elements. As discussed herein switching elementsor selection elements can comprise transistor switching elements. Insome examples, the switching elements or selection elements eachcomprise n-type, p-type, normally-on, or normally-off transistors. Insome examples, the switching elements or selection elements can insteadeach comprise transmission gates, or other switching elements. Also, asused herein, an output node, such as node 325, is an electricalconnection node, which might act as an input node for synaptic/writecurrents and an output node for voltage spike outputs.

FIG. 4 is a waveform diagram presented to illustrate example controlprocesses for the probabilistic neuron circuit elements of FIG. 3.Operations 400 are provided in FIG. 4 which include example voltagewaveforms corresponding to control signals V1-V5 indicated in FIG. 3, aswell as an example output signal (V_(SPIKE)).

At an initial timeframe, between t₀ and t₁, a write phase occurs. Thiswrite phase includes setting associated control voltages to nodes V1-V5to enable I_(WRITE) to flow to perturbation element 322. Specifically,node V1 is set to a high logical level (or V_(DD)) to enable transistor319 and allow V_(SYN) to propagate I_(WRITE) to node 325. I_(WRITE) thencan probabilistically switch a state of perturbation element 322depending on the magnitude and duration of I_(WRITE). Node V2 is set toa low logical level, such as a ground potential or electrical reference,to disconnect or decouple reference element 321 from node V4. Whenreference element 321 is disconnected from node V4, I_(WRITE) influencesthe state of perturbation element 322 and not reference element 321.Node V4 can be coupled to ground throughout all phases of FIG. 4.Typically, reference element 321 is held in a particular, predeterminedmagnetization state, which might be a magnetization state held in anantiparallel state (AP). Node V3 is coupled to V_(DD) to ensure thattransistor 324 is enabled to couple node V5 to perturbation element 322.In the write phase, node V5 is held to ground to allow I_(WRITE) to flowfrom synaptic circuit 310, through node 325, and to a ground potentialat node V5. The write phase has completed when after a duration that isvariable or selectable for a desired state switching behavior ofperturbation element 322.

After the write phase, a read phase commences between t₁ and t₂. Thisread phase allows for checking of the state of perturbation element 322to determine if the state has changed from the initial phase to a finalphase. In the read phase, synaptic circuit 310 is decoupled from neuronelements 320 by disabling transistor 319 by setting node V1 to ground.Node V2 is taken to V_(DD) which couples a terminal associated withpinned layer 352 of reference element 321 to ground at node V4. Node V3remains at V_(DD) while node V5 is briefly driven to a level betweenground and V_(DD). This voltage level is referred to as V_(READ) andproduces a voltage spike at node 325 if perturbation element 322 haschanged state from the initial state. If no change in state oftransistor 324 occurs, then no voltage spike is produced. During theread phase, a small current I_(READ) flows through perturbation element322, node 325, and reference element 321 in series. Reference element321 has a magnetization state held in a predetermined state. Whenperturbation element 322 is switched into an opposite magnetizationstate as reference element 321, an output is produced at node 325. Thisoutput can comprise a voltage spike, which can be further conditioned bylogic inverter 331 to produce V_(SPIKE).

If no voltage spike is produced during the read phase, then anotherwrite phase can occur as described above. Repeated write phases (t₂-t₃)and read phases (t₃-t₄) can occur until a voltage spike is produced asan output. Once the voltage spike is detected, a reset phase (t₄-t₅) canbe performed. The reset phase includes deactivating transistor 319 todecouple synaptic circuit 310 from neuron element 320, which may alreadybe decoupled from a previous read phase. A terminal associated withpinned layer 352 of reference element 321 is coupled to ground at nodeV4, while a terminal associated with pinned layer 355 of perturbationelement 322 is coupled to V_(RESET) at node V5. A small reset currentflows through perturbation element 322, node 325, and reference element321 to induce a state change in perturbation element 322 back to theinitial state. After reset, further write phases (t₅-t₆) and read phases(t₆-t₇) can occur to attempt to change the state of perturbation element322.

The various magnetization states of perturbation element 322 andreference element 321 can comprise either parallel (P) states oranti-parallel (AP) states. In one example, reference element 321 is heldin an AP state, while perturbation element 322 is reset into an initialAP state. If the AP state of perturbation element 322 changes to the Pstate, then a voltage spike is produced when the read current is applieddue in part to the states of perturbation element 322 and referenceelement 321 being in opposite states. If the AP state of perturbationelement 322 does not change to the P state, then a voltage spike is notproduced when the read current is applied, and perturbation element 322remains in the AP state. Alternatively, different initial stateconfigurations might be employed, with associated control voltages V2-V5applied. For example, reference element 321 could instead be held in amagnetization state comprising a P state, while perturbation element 322is reset into a P state. If the initial P state of perturbation element322 changes to the AP state, then a voltage spike is produced when anappropriate read current is applied.

As used herein, the various voltage levels or logic levels are merelyexemplary. Appropriate electrical voltages, reference potentials, andlogic levels can be employed depending upon the circuit configuration,grounding configuration, and surrounding control/logic circuitry. In aspecific example, V_(DD) comprises a logic high level with respect to alogic low comprising a reference potential, ground potential, orreference voltage. V_(DD) might be 3.3 VDC, while logic low might be 0VDC. V_(READ) might be a voltage lower than V_(DD), such as 2.0 VDC,among other voltages. V_(RESET) comprises a higher voltage thanV_(READ), and may comprise V_(DD) or even higher voltages.

To further illustrate the state changes among MTJ elements, FIG. 5 ispresented. FIG. 5 illustrates operation of MTJ elements that switchstates among an anti-parallel (AP) state and parallel (P) state. ExampleMTJ configuration is shown having a pinned layer, tunnel barrier layer,and free layer. The pinned layer typically has a magnetization fixed ina particular orientation, such as shown in FIG. 5. The free layer canchange orientation according to applied currents or voltages. When boththe pinned layer and free layer are in the same magnetic orientation,then the two layers can be considered in the ‘parallel’ state. When thepinned layer and free layer are in different magnetic orientations, thenthe two layers can be considered in the ‘anti-parallel’ state. This MTJconfiguration can be represented schematically as a state-alterableresistor element shown in configuration 500.

To change states among the MTJ, such as by changing relative magneticorientations among the pinned layer and free layer, current pulses canbe applied to the MTJ. Graph 501 illustrates one example state changearrangement. Graph 501 shows how application of a synaptic/write current(I_(WR)), an MTJ can be placed from an initial AP state into asubsequent P state, and from an initial P state into a subsequent APstate. Hysteresis-like behavior is exhibited, where a sufficientmagnitude and duration of the write current is needed to change thestate of the MTJ once it has changed into another state. The various Pand AP states have an associated resistance (R_(MTJ)) associatedtherewith, indicated by the vertical axis in graph 501. In graph 501,the AP state has a high associated resistance (R_(AP)) relative to the Pstate, while the P state has a low associated resistance (R_(P))relative to the AP state. These resistance changes can be utilized toproduce an output spike responsive to a read current, as discussedherein, when a perturbation MTJ is in a different state relative to areference MTJ.

As mentioned above, a magnitude and duration of the write current caninfluence the state change timing. Typically, a current pulse or pulsetrain is applied to an MTJ to attempt to change the state of the MTJ. Asseen in graph 503, this current pulse can have a pulse width and pulseamplitude. The pulse width can be represented in seconds (or nanosecondsin FIG. 5), while the pulse amplitude can be represented in a voltage oramperage. FIG. 5 illustrates a voltage amplitude, which can induce awrite current for the MTJ. Insufficient pulse width or pulse amplitudecan lead to non-switching of the state of the MTJ, as associatedmagnetization starts leaking once the applied pulse is removed. Asufficient pulse width or pulse amplitude, or a sufficient series ofpulses, can lead to switching of states by the MTJ. Thus, the MTJ canemulate behavior of a biological neuron. The firing or “spiking” of abiological neuron, which occurs when neuron cell membrane potentialcrosses a threshold, is equivalent to the switching of the MTJ. Randomthermal fluctuation in an MTJ can be utilized for generating randombits. Switching probability is a strong function of the appliedperturbation voltage and perturbation pulse width. Once the artificialneuron (MTJ) “spikes,” the MTJ has to be reset back to the initialstate. Hence, the operation of the neuron MTJ can be resolved into twocycles, namely a “write” phase followed by a “read” phase indicatedabove.

Graph 503 of FIG. 5 provides an illustration of characterization ofbehavior of an MTJ under various pulse widths (in nanoseconds) along thevertical axis and various pulse amplitudes (in voltage) along thehorizontal axis. A 50% contour line 504 is shown to illustrate anexample characteristic behavior of a true random number generator (TRNG)behavior of an MTJ for a range of pulse widths and pulse amplitudes.Each contour shade indicates a region of associated switchingprobability for an MTJ from an AP state to a P state. The varioussynaptic currents or neuron write currents discussed herein can betailored to suit a desired behavior indicated by graph 503, such as aTRNG behavior, among others.

Turning now to further implementations of artificial neurons comprisingMTJs, FIG. 6 is presented. FIG. 6 illustrates example array of neuroncircuits formed on a semiconductor substrate. This example array mightcomprise a magneto-resistive random-access memory (MRAM) array formedalong with various control logic, interconnect, or other circuitry. Insome examples, an MRAM array will have wordlines and bitlines comprisedof MRAM devices spanning horizontally with respect to a substrate. Otherarray configurations and arrangements of MRAM arrays and associatedcontrol/interconnect logic can instead be formed than that shown in FIG.6, such as vertically stacked arrays.

Three views 600-602 are presented in FIG. 6. View 600 illustrates a sideview of an example MRAM array with various control logic layers 642formed up in a ‘z’ direction on semiconductor substrate 650.Interconnect layers 641 and MRAM/MTJ layers 640 are formed at least inpart onto logic layers 642. Interconnect layers 641 comprise variousmetallization, metal layers, and other various interconnect to coupleMRAM/MTJ elements to elements of logic layers 642. View 601 illustratesa top view of an MRAM array which is formed horizontally in the ‘x’ and‘y’ directions onto logic layers 642. Interconnect layers 641 areomitted for clarity in view 601. View 602 presents an overview of asemiconductor wafer 690 spanning horizontally in ‘x’ and ‘y’ directions,which can have various semiconductor, metallization, and otherassociated structures built up in a vertical (‘z’) direction which formelements 640-642 and 650.

In view 601, MRAM bitlines (611-617) are formed horizontally, and maycomprise MTJs, for example. MRAM bitlines (611-617) can have senseamplifiers or other read circuitry positioned at an end of each MRAMbitline. However, in this example, instead of (or in addition to) thisread circuitry, a neuron circuit is added to each bitline. This neuroncircuits (621-627) fits within the pitch of each associated bitline. Theneuron circuitry can comprise element illustrated in FIG. 3, such asneuron elements 320, output elements 330, and in some cases, a switchingelement between the bitline and the neuron elements (such as transistor319 of FIG. 3).

Thus, an array of neuron bitlines 610 can be provided in view 601 ofFIG. 6. Each neuron circuit 621-627 can be fed a synaptic currentproduced by an associated MRAM bitlines 611-617. This array can beformed along with other elements, such as metallization, interconnect,control circuitry, and logic used to interconnect, control, andotherwise interface with each neuron bitline. Elements of control system140 can be included in control logic 642 and interconnect 641. Theseelements can be formed, as illustrated in view 600, onto a semiconductorsubstrate 650 using techniques found in semiconductor wafer processingand microfabrication, such as photo-lithography, diffusing, deposition,epitaxial growth, etching, annealing, and ion implanting, among others.

Furthermore, each of the neuron bitlines can be interconnected, such asusing interconnect 641 in view 600. Outputs from individual neuronbitlines can be used as inputs to other neuron bitlines. Complexinterconnections can be formed, and dynamic interconnection can beprovided using interconnect 641 and control logic 642, among otherelements. In this manner, an artificial neural network (ANN) can beformed using bitlines with neuron circuits included in vertical pitch ofeach bitline. In yet further examples, outputs of each neuron circuitcan be provided to a microprocessor, central processing unit, graphicsprocessing unit, application-specific integrated circuitry, orfield-programmable gate array, among other circuitry, for processing anddynamic interconnection.

In some implementations of the systems, circuitry, and elementsdiscussed herein, a stochastic circuit can be established. Thisstochastic circuit can include a means for selectively producing asynaptic current from a source circuit though a perturbation elementcoupled to a node to stochastically influence a state change of theperturbation element from an antiparallel magnetization state to aparallel magnetization state. The stochastic circuit can also include ameans for selectively producing a read current through the perturbationelement and a reference element coupled by the node. The stochasticcircuit can also include a means for producing an output at the noderepresentative of a present magnetization state of the perturbationelement. The stochastic circuit can also include a means for selectivelyproducing a reset current through the perturbation element and thereference element coupled by the node to place the perturbation elementinto an initial state comprising the antiparallel magnetization state.

The means for selectively producing the synaptic current can compriseany of synaptic circuit 110, control system 140, one or more links 161,link 165, write current source 310, synaptic bitline 340, transistorswitch 319, MRAM bitlines 611-617, logic layers 640, and interconnect641, among other elements discussed herein. The means for selectivelyproducing the read current can comprise any of control system 140, links162, neuron circuit 120, transistors 323-324, MTJ elements 321-322, node325, and logic layers 640, among other elements discussed herein. Themeans for producing an output at the node can comprise any of neuroncircuit 120, link 162, link 166, link 163, output circuit 130,transistors 323-324, MTJ elements 321-322, node 325, output elements330, inverter 331, and logic layers 640, among other elements discussedherein. The means for selectively producing a reset current can compriseany of neuron circuit 120, link 162, link 166, link 163, output circuit130, transistors 323-324, MTJ elements 321-322, node 325, outputelements 330, inverter 331, and logic layers 640, among other elementsdiscussed herein.

The included descriptions and figures depict specific embodiments toteach those skilled in the art how to make and use the best mode. Forthe purpose of teaching inventive principles, some conventional aspectshave been simplified or omitted. Those skilled in the art willappreciate variations from these embodiments that fall within the scopeof the disclosure. Those skilled in the art will also appreciate thatthe features described above can be combined in various ways to formmultiple embodiments. As a result, the invention is not limited to thespecific embodiments described above, but only by the claims and theirequivalents.

What is claimed is:
 1. A circuit comprising: a perturbation magnetictunnel junction (MTJ) element; a reference element; an output nodecoupling a free layer of the perturbation MTJ element and a firstterminal of the reference element to a synaptic current source, whereinthe synaptic current source comprises a plurality of MTJ elementsconnected in parallel and a selection element to selectively couple asynaptic current from the plurality of MTJ elements to the output node;a read current source coupled to a pinned layer of the perturbation MTJelement; and a reference potential coupled to a second terminal of thereference element.
 2. The circuit of claim 1, wherein the perturbationMTJ element comprises a first perpendicular spin transfer torque (STT)MTJ element having an alterable magnetization state, and wherein thereference element comprises a second perpendicular STT MTJ with amagnetization state held in a predetermined state.
 3. The circuit ofclaim 1, wherein the synaptic current source comprises at least a firstselection element to selectively couple a synaptic current to the outputnode, wherein the read current source comprises at least a secondselection element to selectively couple one of a read current and areset current to the pinned layer of the perturbation MTJ element, andwherein circuitry supplying the reference potential comprises a thirdselection element to selectively couple an electrical reference to thesecond terminal of the reference element.
 4. The circuit of claim 1,wherein the perturbation MTJ element and the reference element form avoltage divider having an output voltage at the output node.
 5. Anapparatus comprising: a perturbation magnetic tunnel junction (MTJ)element coupled to a control line through a node; and a reference MTJelement coupled to the control line through the node; wherein during asynaptic phase, the perturbation MTJ element changes stateprobabilistically in response to a synaptic current provided by thecontrol line through the node; and wherein during a read phase, a readcurrent established between the perturbation MTJ element and thereference MTJ element results in an output at the node representative ofthe state of the perturbation MTJ element wherein a synaptic currentsource that feeds the control line comprises a plurality of MTJ elementscoupled in parallel, and a selection element to selectively couple asynaptic current from the plurality of MTJ elements to the node.
 6. Theapparatus of claim 5, wherein the output comprises a voltage spike atthe node that results from passing the read current through at least theperturbation MTJ element when the perturbation MTJ element is in anopposite magnetization state relative to the reference MTJ element. 7.The apparatus of claim 5, wherein the read current is introduced to aterminal of the perturbation MTJ element opposite the node, wherein aterminal of the reference MTJ element opposite the node is coupled to aground potential to form a voltage divider between the perturbation MTJelement and the reference MTJ element, and wherein the output comprisesa voltage spike resultant from the read current based on a magnetizationstate of at least the perturbation MTJ element.
 8. The apparatus ofclaim 5, wherein a free layer of the perturbation MTJ element is coupledto the node, and a free layer of the reference MTJ is coupled to thenode.
 9. The apparatus of claim 5, further comprising: responsive to areset current established through at least the perturbation MTJ element,the perturbation MTJ element is reset into an antiparallel magnetizationstate, and wherein the reference MTJ element comprises a magnetizationstate held in an antiparallel state.
 10. The apparatus of claim 5,wherein an alternating application of the synaptic current and the readcurrent is repeated until a voltage spike at the node is produced as theoutput responsive to the read current.
 11. The apparatus of claim 5,wherein varying properties of the synaptic current provided by theplurality of MTJ elements influences a probabilistic behavior of theperturbation MTJ element.
 12. A method comprising: during a write phase,sending a synaptic current from a source circuit through a perturbationmagnetic tunnel junction (MTJ) element coupled to a node tostochastically influence a magnetization state of the perturbation MTJelement, wherein the source circuit comprises a plurality of MTJelements connected in parallel and a selection element to selectivelycouple the synaptic current from the plurality of MTJ elements to thenode; and during a read phase, isolating the source circuit from thenode, sending a read current through the perturbation MTJ element and areference MTJ element coupled by the node, and producing an outputvoltage at the node representative of the magnetization state of theperturbation MTJ element.
 13. The method of claim 12, furthercomprising: repeating the write phase and the read phase until a voltagespike occurs at the node during the read phase indicating a change inthe magnetization state of the perturbation MTJ element from an initialmagnetization state to an opposite magnetization state relative to thereference MTJ element.
 14. The method of claim 13, further comprising:during a reset phase, sending a reset current through the perturbationMTJ element and the reference MTJ element coupled by the node to placethe perturbation MTJ element into the initial state comprising anantiparallel magnetization state.
 15. The method of claim 12, furthercomprising: during the read phase, introducing the read current to aterminal of the perturbation MTJ element opposite the node, and couplinga terminal of the reference MTJ element opposite the node to a groundpotential.
 16. The method of claim 12, further comprising: during thewrite phase, sending the synaptic current from the plurality of MTJelements coupled in parallel, wherein the plurality of MTJ elements eachoutput a corresponding portion of the synaptic current thatstochastically influences a change in the magnetization state of theperturbation MTJ element.
 17. A system to produce a probabilisticoutput, comprising: a synaptic current source comprising: a plurality ofmagnetic tunnel junction (MTJ) elements that together provide a synapticcurrent; a first switching element configured to selectively provide thesynaptic current to a node of a neuron circuit during a write phase; theneuron circuit comprising: a perturbation MTJ element; a reference MTJelement; the node coupling a free layer of the perturbation MTJ elementand a free layer terminal of the reference MTJ element, wherein anoutput produced at the node during a read phase comprises theprobabilistic output; a second switching element configured to couple aread potential to a pinned layer of the perturbation MTJ element duringthe read phase and couple a reference potential to the pinned layer ofthe perturbation MTJ element during the write phase; and a thirdswitching element configured to couple the reference potential to apinned layer of the reference MTJ element during the read phase anddecouple the reference potential from the pinned layer of the referenceMTJ during the write phase.
 18. The system of claim 17, wherein: thesecond switching element is further configured to couple a resetpotential to the pinned layer of the perturbation MTJ element during areset phase; and the third switching element is further configured tocouple the pinned layer of the reference MTJ element to the referencepotential during the reset phase.
 19. The system of claim 17, furthercomprising: an output element configured to present an output voltageindicating the probabilistic output, wherein a first output voltagelevel indicates at least the perturbation MTJ element wasprobabilistically placed in an opposite magnetization state relative tothe reference MTJ element responsive to the synaptic current.
 20. Thesystem of claim 17, wherein magnitude and duration properties of thesynaptic current provided by the synaptic current source influences aprobabilistic magnetization state change in the perturbation MTJelement.
 21. The system of claim 17, wherein the perturbation MTJelement undergoes a probabilistic magnetization state change in responseto the synaptic current and at least thermal noise present in theperturbation MTJ element.
 22. The system of claim 17, furthercomprising: interconnect elements configured to interconnect an outputrepresenting the probabilistic output produced at the node as an inputto one or more other synaptic current sources associated with one ormore further neuron circuits.
 23. A stochastic device comprising: meansfor selectively producing a synaptic current through a perturbationelement coupled to a node to stochastically influence a state change ofthe perturbation element from an antiparallel magnetization state to aparallel magnetization state; and means for selectively producing a readcurrent through the perturbation element and a reference element coupledwith the perturbation element by the node; and means for producing anoutput at the node representative of a present magnetization state ofthe perturbation element.
 24. The stochastic device of claim 23, furthercomprising: means for selectively producing a reset current through theperturbation element and the reference element coupled by the node toplace the perturbation element into an initial state comprising theantiparallel magnetization state.